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In this paper, a stochastic SIRV epidemic model with general nonlinear incidence and vaccination is investigated. The value of our study lies in two aspects. Mathematically, with the help of Lyapunov function method and stochastic analysis theory, we obtain a stochastic threshold of the model that completely determines the extinction and persistence of the epidemic. Epidemiologically, we find that random fluctuations can suppress disease outbreak, which can provide us some useful control strategies to regulate disease dynamics. In other words, neglecting random perturbations overestimates the ability of the disease to spread. The numerical simulations are given to illustrate the main theoretical results.

The present study aims to compare the quality of soil of different region of Haridwar with reference to physicochemical and heavy metal parameters. To fulfill the objectives of present study, soil sampling was performed in forest (control site), industrial, residential and agricultural areas in and around Haridwar. Soil samples were analyzed for different physicochemical and heavy metal parameters. Values of all the studied soil parameters were found highest (an increase of 32% in temperature (16.63 to 21.640C), 121% in soil moisture (13.05 to 28.39%), 29.02% in soil porosity (37.56 to 49.03%), and 19.6% in the water holding capacity (36.22 to 43.58%), 74.18% in conductivity (0.25 to 0.40 µMhos/cm), and 203.78% in chloride (16.67 to 53.97mg/gm)) at the industrial area in comparison to other sites. During the course of the study, an increasing trend in all the parameters at all the sites was observed this may be due to the dumping of industrial solid waste and effluent. Although no negative impact was observed on the soil quality but continuous dumping will results in harmful impacts due to the accumulation of pollutants. Therefore there is a need for safe and proper disposal and utilization techniques to manage the enormous quantity of industrial waste. All the heavy metals (such as copper (0.050 to 0.055mg/gm), manganese (0.232 to 0.242mg/gm), nickel (0.035 to 0.036mg/gm), lead (0.039mg/gm), and iron (1.19 to 1.22) were found in higher concentration during the study period while cadmium was found absent during the study period.

Environmental obligation, fuel security, and human health issues have fuelled the search for locally produced sustainable transport fuels as an alternative to liquid petroleum. This study evaluates the sustainability performance of various alternative energy sources, namely, ethanol, electricity, electricity-gasoline hybrid, and hydrogen, for Western Australian road transport using a life cycle sustainability assessment (LCSA) framework. The framework employs 11 triple bottom line (TBL) sustainability indicators and uses threshold values for benchmarking sustainability practices. A number of improvement strategies were devised based on the hotspots once the alternative energy sources failed to meet the sustainability threshold for the determined indicators. The proposed framework effectively addresses the issue of interdependencies between the three pillars of sustainability, which was an inherent weakness of previous frameworks. The results show that the environment-friendly and socially sustainable energy options, namely, ethanol-gasoline blend E55, electricity, electricity-E10 hybrid, and hydrogen, would need around 0.02, 0.14, 0.10, and 0.71 AUD/VKT of financial support, respectively, to be comparable to gasoline. Among the four assessed options, hydrogen shows the best performance for the environmental and social bottom line when renewable electricity is employed for hydrogen production. The economic sustainability of hydrogen fuel is, however, uncertain at this stage due to the high cost of hydrogen fuel cell vehicles (HFCVs). The robustness of the proposed framework warrants its application in a wide range of alternative fuel assessment scenarios locally as well as globally.

In light of increasingly rapid climate change worldwide, and with the purpose to reduce financial losses for dairy farmers and enable a more sustainable farming, the necessity to implement breeding values for heat resistance in breeding strategies, has become more and more pronounced. Estimation of breeding values requires determination of temperature-humidity index (THI) threshold value. Therefore, the objective of this paper was to determine temperature-humidity index (THI) threshold values for daily milk yield, daily fat and protein content of milk produced by Holsteins and dairy Simmentals in Croatian farms. With that purpose, 1, 070, 554 test-day records from 70, 135 Holsteins reared on 5, 679 farms and 1, 300, 683 test-day records from 86, 013 Simmentals reared on 8, 827 farms in Croatia were compared to records of ambient temperature and relative humidity collected in the barn, during regular milking recordings from January 2005 to December 2012. Based on this analysis the following conclusions could be drawn: threshold values for daily milk yield highly depends on parity and breed (Holsteins: 68, 69 and 72 for 1st, 2nd, 3+ parity ; Simmentals: 77 for 1st) ; daily fat and protein contents showed a highly significant decrease due to heat stress condition (THI in 66 – 80) in both, Holstein and Simmental cows, and in all parity classes ; multiparous cows were more resistant to heat stress than primiparous ; Simmental cows were more resistant to heat stress than Holsteins.

A stochastic susceptible–infectious–recovered epidemic model with temporary immunity and media coverage is proposed. The effects of Lévy jumps on the dynamics of the model are considered. A unique global positive solution for the epidemic model is obtained. Sufficient conditions are derived to guarantee that the epidemic disease is extinct and persistent in the mean. The threshold behavior is discussed. Numerical simulations are given to verify our theoretical results.

We consider existence and multiplicity results for a semilinear problem driven by the square root of the negative Laplacian in presence of a nonlinear term which is the difference of two powers. In the case of convex–concave powers, a precise description of the problem at the threshold value of a given parameter is established through variational methods and truncation techniques.

In computer network security, IP address spoofing plays a major role in the creation of Internet Protocol (IP) packets with a fake or forged source IP address and this may lead to major attacks to cloud centre. When the identities of user information are forged by spoofing or masquerade as another computing system. Whether the basic protocol for sending data in the Internet communication are based on the Internet Protocol (“IP”). In network communication header of each IP packet consist of source and destination address of the packet. The source address contains where the packet was sent origin address. In that IP spoofing can be performed by forging the original header from sender it act like packet is sent from origin with different address, an attacker can make it appear that the packet was sent by a different machine. So that the IP Spoofing attack can be placed to further attacks comes into place of impersonating system. This can avoided by a novel solution, named Passive IP Trace back (PIT), to avoid the challenges in operation. To capture the origins of IP spoofing traffic is difficult to locate. As long as the real locations of spoofing are not identified, they cannot be determined from launching further attacks. Identifying the origins of spoofing traffic can help build a reputation system for network place, which would be helpful to push the corresponding ISPs to verify IP source address.

Agricultural soils with too little soil organic matter (SOM) content are characterized by fertility problems. A number of authors have tried to specify threshold values for SOM content to indicate what is ‘too little’, ranging from 1 to 5%, below which yields may be affected. How much SOM content is sufficient, however, depends on a number of environmental factors. In addition, up to date farmers’ perceptions were not included when developing thresholds. Therefore, this study focuses on the following three objectives: (1) to identify a risk indicator on SOM deficiency based on environmental factors and agricultural land use; (2) to test the risk indicator using farmers’ perceptions and (3) to establish threshold values for SOM content based on farmers’ perceptions. For objective 1, literature was reviewed on effects of environmental factors and land use on SOM deficiency. Findings were combined into nine options for a risk indicator on SOM deficiency, mapped at European scale. For objective 2, a farm survey was done among 1452 arable farmers in five European countries (Belgium, Germany, Austria, Spain and Italy). Associations between perceived deficiency of SOM by farmers and environmental factors, land use and the risk indicator were investigated. For objective 3, farmers’ perceptions on SOM deficiency were related to the average SOM content of their fields. Mapping the risk indicator at European scale gives a high to very high risk of SOM deficiency for 7 to 37% of European agricultural land, mainly located in Southern and Eastern Europe. Of the farmers in our survey, 18% perceived a high to very high SOM deficiency. A weak correlation was found between the risk indicator and farmers’ perceptions of SOM deficiency (0.15-0.18, Spearman’s rank correlation). Stronger relations were found between separate environmental factors and perceived SOM deficiency. Apparently, having a more extreme environmental condition for one factor gives a higher chance of perceiving a deficiency of SOM than a combination of moderate environmental conditions. Based on farmers’ perceptions threshold intervals for SOM content were established (sand: 1.2–4.7%, loam: 0.6–2.6% and clay: 1.0–2.4%). If policies on SOM management want to include benefits for productive capacity, targeting areas with a relatively high risk of SOM deficiency, more extreme environmental conditions or with very low SOM contents (below the given threshold intervals) seems most promising.

To detect the small island effect (SIE) and nestedness patterns of herpetofauna of the West Indies, we derived and updated data on the presence/absence of herpetofauna in this region from recently published reviews. We applied regression‐based analyses, including linear regression and piecewise regressions with two and three segments, to detect the SIE and then used the Akaike's information criterion (AIC) as a criterion to select the best model. We used the NODF (a nestedness metric based on overlap and decreasing fill) to quantify nestedness and employed two null models to determine significance. Moreover, a random sampling effort was made to infer about the degree of nestedness at portions of the entire community. We found piecewise regression with three segments performed best, suggesting the species–area relationships possess three different patterns that resulted from two area thresholds: a first one, delimiting the SIE, and a second one, delimiting evolutionary processes. We also found that taxa with lower resource requirement, higher dispersal ability, and stronger adaptation to the environment generally displayed lower corresponding threshold values, indicating superior taxonomic groups could earlier end the SIE period and start in situ speciation as the increase of island size. Moreover, the traditional two‐segment piecewise regression method may cause poor estimations for both slope and threshold value of the SIE. Therefore, we suggest previous SIE detection works that conducted by two‐segment piecewise regression method, ignoring the possibility of three segments, need to be reanalyzed. Antinestedness occurred in the entire system, whereas high degree of nestedness could still occur in portions within the region. Nestedness may still be applicable to conservation planning at portions even if it is antinested at the regional scale. However, nestedness may not be applicable to conservation planning at the regional scale even if nestedness does exist among sampling islands from a portion.

The purpose of this study is to identify factors that can change the environmental friendliness of individuals in the context of climate change issues in terms of values, beliefs, controllability, concern, attitude, intention, and behavior through a survey experiment, and to test the hypothesis that providing information about the amount of carbon dioxide (CO2) emissions attributable to an individual with its threshold value motivates him/her to reduce that amount using statistical analyses (the Mann–Whitney test) and multivariate regressions (the ordered logit model). It is crucial to change the behavior of individuals as well as organizations to reduce the emissions of CO2 for solving climate change issues, because the aggregate amount of individual CO2 emissions is too large to ignore. We conducted a survey experiment to detect factors affecting the environmental friendliness of individuals. Subjects of the experiment were 102 students at Shiga University in Japan. They were randomly provided with communication opportunities, information about individual or group CO2 emissions, and information about their threshold value. The finding is that provision of information about the amount of individual and group CO2 emissions may be able to improve that person’s environmental friendliness in terms of values, beliefs, concern, attitude, intention, and behavior.

Similar to other epidemics, the novel coronavirus (COVID-19) spread very fast and infected almost two hundreds countries around the globe since December 2019. The unique characteristics of the COVID-19 include its ability of faster expansion through freely existed viruses or air molecules in the atmosphere. Assuming that the spread of virus follows a random process instead of deterministic. The continuous time Markov Chain (CTMC) through stochastic model approach has been utilized for predicting the impending states with the use of random variables. The proposed study is devoted to investigate a model consist of three exclusive compartments. The first class includes white nose based transmission rate (termed as susceptible individuals), the second one pertains to the infected population having the same perturbation occurrence and the last one isolated (quarantined) individuals. We discuss the model’s extinction as well as the stationary distribution in order to derive the the sufficient criterion for the persistence and disease’ extinction. Lastly, the numerical simulation is executed for supporting the theoretical findings.

Image thresholding is one of the fastest and most effective methods of detecting objects in infrared images. This paper proposes an infrared image thresholding method based on the functional approximation of the histogram. The one-dimensional histogram of the image is approximated to the transient response of a first-order linear circuit. The threshold value for the image segmentation is formulated using combinational analogues of standard operators and principles from the concept of the transient behavior of the first-order linear circuit. The proposed method is tested on infrared images gathered from the standard databases and the experimental results are compared with the existing state-of-the-art infrared image thresholding methods. We realized through the experimental results that our method is well suited to perform infrared image thresholding.

Data mining is the process of finding structure of data from large data sets. With this process, the decision makers can make a particular decision for further development of the real-world problems. Several data clusteringtechniques are used in data mining for finding a specific pattern of data. The K-means method isone of the familiar clustering techniques for clustering large data sets. The K-means clustering method partitions the data set based on the assumption that the number of clusters are fixed.The main problem of this method is that if the number of clusters is to be chosen small then there is a higher probability of adding dissimilar items into the same group. On the other hand, if the number of clusters is chosen to be high, then there is a higher chance of adding similar items in the different groups. In this paper, we address this issue by proposing a new K-Means clustering algorithm. The proposed method performs data clustering dynamically. The proposed method initially calculates a threshold value as a centroid of K-Means and based on this value the number of clusters are formed. At each iteration of K-Means, if the Euclidian distance between two points is less than or equal to the threshold value, then these two data points will be in the same group. Otherwise, the proposed method will create a new cluster with the dissimilar data point. The results show that the proposed method outperforms the original K-Means method.

We introduce a score-type statistic to test for a non-zero regression coefficient when the relevant term involves a nuisance parameter present only under the alternative. Despite the non-regularity and complexity of the problem and unlike the previous approaches, the proposed test statistic does not require the nuisance to be estimated. It is simple to implement by relying on the conventional distributions, such as Normal or t, and it justified in the setting of probabilistic coherence. We focus on testing for the existence of a breakpoint in segmented regression, and illustrate the methodology with an analysis on data of DNA copy number aberrations and gene expression profiles from 97 breast cancer patients; moreover some simulations reveal that the proposed test is more powerful than its competitors previously discussed in literature.

Landfills are one of the most recurrent sources of groundwater contamination worldwide. In order to limit their impacts on groundwater resources, current environmental regulations impose the adoption of proper measures for the protection of groundwater quality. For instance, in the EU member countries, the calculation of trigger levels for identifying significant adverse environmental effects on groundwater generated by landfills is required by the Landfill Directive 99/31/EC. Although the derivation of trigger levels could be relatively easy when groundwater quality data prior to the construction of a landfill are available, it becomes challenging when these data are missing and landfills are located in areas that are already impacted by historical contamination. This work presents a methodology for calculating trigger levels for groundwater quality in landfills located in areas where historical contaminations have deteriorated groundwater quality prior to their construction. This method is based on multivariate statistical analysis and involves 4 steps: (a) implementation of the conceptual model, (b) landfill monitoring data collection, (c) hydrochemical data clustering and (d) calculation of the trigger levels. The proposed methodology was applied on a case study in northern Italy, where a currently used lined landfill is located downstream of an old unlined landfill and others old unmapped waste deposits. The developed conceptual model stated that groundwater quality deterioration observed downstream of the lined landfill is due to a degrading leachate plume fed by the upgradient unlined landfill. The methodology led to the determination of two trigger levels for COD and NH4-N, the former for a zone representing the background hydrochemistry (28 and 9 mg/L for COD and NH4-N, respectively), the latter for the zone impacted by the degrading leachate plume from the upgradient unlined landfill (89 and 83 mg/L for COD and NH4-N, respectively) This work presents a methodology for calculating trigger levels for groundwater quality in landfills located in areas where historical contaminations have deteriorated groundwater quality prior to their construction. This method is based on multivariate statistical analysis and involves 4 steps: (a) implementation of the conceptual model, (b) landfill monitoring data collection, (c) hydrochemical data clustering and (d) calculation of the trigger levels. The proposed methodology was applied on a case study in northern Italy, where a currently used lined landfill is located downstream of an old unlined landfill and others old unmapped waste deposits. The developed conceptual model stated that groundwater quality deterioration observed downstream of the lined landfill is due to a degrading leachate plume fed by the upgradient unlined landfill. The methodology led to the determination of two trigger levels for COD and NH4-N, the former for a zone representing the background hydrochemistry (28 and 9 mg/L for COD and NH4-N, respectively), the latter for the zone impacted by the degrading leachate plume from the upgradient unlined landfill (89 and 83 mg/L for COD and NH4-N, respectively).

International audience; In a previous study, the Comet assay was optimized for Palaemon serratus prawns in order to propose a biomarker for sperm quality in this species. However, better knowledge of its basal level and its natural variability, related to intrinsic biotic and environmental abiotic factors, is required before any relevant use of this biomarker in the field. To fulfill this goal, the present study proceeded in three steps: (i) the temporal variability of DNA integrity was followed monthly in a reference population over a 2-year period, (ii) the correlation between the main intrinsic biotic (i.e. size, weight and molting stage) and abiotic factors (i.e. water temperature) were recorded in the field, and the basal DNA integrity was assessed in order to scrutinize any confounding influence of factors unrelated to toxic response, (iii) the baseline level was used to discriminate biomarker response among different stations displaying contrasting contamination levels. The results of the two-year monitoring in the reference population revealed no correlation between the levels of spermatozoa DNA damage and temperature, body size, weight or molting stage. Only a slight variability between monthly samplings was detected. On the basis of these field-collected data, we defined a reference distribution (i.e. 52.6 ± 5.6 A.U) with a threshold value (i.e. 61.7 A.U). Finally, this threshold value proved its relevance to discriminate among stations with contrasting pollution levels around the Seine Bay. Indeed, the results suggest significant DNA damage in populations nearest the Seine estuary, a major source of contaminants in the Bay, and a lower effect in populations further away from the estuary. The overall conclusion was that the Comet assay on P. serratus spermatozoa could be a useful tool for the monitoring of the toxicological print within sperm and main globally the contamination exposure of crustaceans in marine waters

In this paper, we establish a discrete-time analog for coupled within-host and between-host systems for an environmentally driven infectious disease with fast and slow two time scales by using the non-standard finite difference scheme. The system is divided into a fast time system and a slow time system by using the idea of limit equations. For the fast system, the positivity and boundedness of the solutions, the basic reproduction number and the existence for infection-free and unique virus infectious equilibria are obtained, and the threshold conditions on the local stability of equilibria are established. In the slow system, except for the positivity and boundedness of the solutions, the existence for disease-free, unique endemic and two endemic equilibria are obtained, and the sufficient conditions on the local stability for disease-free and unique endemic equilibria are established. To return to the coupling system, the local stability for the virus- and disease-free equilibrium, and virus infectious but disease-free equilibrium is established. The numerical examples show that an endemic equilibrium is locally asymptotically stable and the other one is unstable when there are two endemic equilibria.

The aging of electrical insulation material or a system is a main issue for designers of high-voltage (HV) machines. Precise determination of the life cycle of electrical insulation is one way of improving the efficiency of electrical machines involved in the production and transmission of electrical energy. Much effort has been devoted to preparing statistical or physical methods of Electrical Insulating System (EIS) life time estimation in the real operation of electrical machinery. The main aim of this paper is to introduce a new physical-statistical model of thermal aging respecting the threshold value. This model is based on thermal aging model and the main difference between this model and previously published models is taking into account the threshold value of degradation factor. The complete design of this model is presented in this paper, including functions defining the threshold value of the effect of the degradation factor depending on the temperature. Proposed model was verified by accelerated thermal aging test at selected temperatures (160, 170, 180 °C) and time intervals (0, 120, 240 h) on a commonly used transformer board. The breakdown voltage was set as an indicating parameter of the level of thermal aging and was measured according to standard IEC 60243-1. Collected data from these measurements were used for threshold value determination (431.23 K) and verification of proposed physical-statistical model of thermal aging respecting the threshold value.

Many hydrological algorithms have been developed to automatically extract drainage networks from DEM, and the D8 algorithm is widely used worldwide to delineate drainage networks and catchments. The simulation accuracy of the SWAT model depends on characteristics of the watershed, and previous studies of DEM resolution and its impacts on drainage network extraction have not generally considered the effects of resolution and threshold value on uncertainty. In order to assess the influence of different DEM resolutions and drainage threshold values on drainage network extraction using the SWAT model, 10 basic watershed regions in China were chosen as case studies to analyse the relationship between extracted watershed parameters and the threshold value. SRTM DEM data at 3 different resolutions were used in this study, and regression analysis for DEM resolution, threshold value and extraction effects was done. The results show that DEM resolution influences the selected flow accumulation threshold value; the suitable flow accumulation threshold value increases as the DEM resolution increases, and shows greater variability for basins with lower drainage densities. The link between drainage area threshold value and stream network extraction results was also examined, and showed a variation trend of power function y = ax b between the sub-basin counts and threshold value, i.e., the maximum reach length increases while the threshold value increases, and the minimum reach length shows no relation with the threshold value. The stream network extraction resulting from a 250 m DEM resolution and a 50 000 ha threshold value was similar to the real stream network. The drainage network density and the threshold value also shows a trend of power function y = ax b ; the value of b is usually 0.5. Keywords: SWAT, digital elevation model (DEM), watershed delineation, threshold value

In this paper, we investigate the dynamical behavior for a stochastic SIS epidemic model with isolation which is as an important strategy for the elimination of infectious diseases. It is assumed that the stochastic effects manifest themselves mainly as fluctuation in the transmission coefficient, the death rate and the proportional coefficient of the isolation of infective. It is shown that the extinction and persistence in the mean of the model are determined by a threshold value R0S. That is, if R0S1, then the disease is stochastic persistent in the means with probability one. Furthermore, the existence of a unique stationary distribution is discussed, and the sufficient conditions are established by using the Lyapunov function method. Finally, some numerical examples are carried out to confirm the analytical results., Highlights • A stochastic SIS epidemic model with isolation and multiple noises perturbation is proposed. • The criteria on the extinction and persistence in the mean with probability one are obtained. • The sufficient conditions for the existence of unique stationary distribution are established.

Aquiclude plays a critical role in the occurrence of mining-induced roof water inrush in underground coal mines. This paper proposes an assessment index for the evaluation of aquiclude stability and a threshold value of water inrush from the roof, based on a case study of roof water inrush accidents in Cuimu coal mine, China. The relation between roof water inrush and water level variation in the aquifer, and the characteristics of aquiclude deformation, were studied in this assessment. Using the developed assessment criteria, the likelihood of roof water inrush was categorized into different risk levels, which were followed by a proposal for roof water inrush control measures. The main findings of this study are: a) in Cuimu coal mine, the waterbody in the bed separation between the upper aquifer and the aquiclude directly causes the inrush, and inrush occurs after the water level declines in the aquifer, b) tension-induced horizontal strains of aquiclude can be regarded as the index to evaluate the stability of aquiclude affected by underground coal mining&mdash, roof water inrush occurs when the maximum horizontal strain reaches a threshold of 10mm/m&mdash, c) based on the critical mining height for aquiclude instability, and the different thicknesses of barrier layers, high-risk zones are identified and inrush controls are proposed.

Background Bioseparations can contribute to more than 70% in the total production cost of a bio-based chemical, and if the desired chemical is localized intracellularly, there can be additional challenges associated with its recovery. Based on the properties of the desired chemical and other components in the stream, there can be multiple feasible options for product recovery. These options are composed of several alternative technologies, performing similar tasks. The suitability of a technology for a particular chemical depends on (1) its performance parameters, such as separation efficiency; (2) cost or amount of added separating agent; (3) properties of the bioreactor effluent (e.g., biomass titer, product content); and (4) final product specifications. Our goal is to first synthesize alternative separation options and then analyze how technology selection affects the overall process economics. To achieve this, we propose an optimization-based framework that helps in identifying the critical technologies and parameters. Results We study the separation networks for two representative classes of chemicals based on their properties. The separation network is divided into three stages: cell and product isolation (stage I), product concentration (II), and product purification and refining (III). Each stage exploits differences in specific product properties for achieving the desired product quality. The cost contribution analysis for the two cases (intracellular insoluble and intracellular soluble) reveals that stage I is the key cost contributor (>70% of the overall cost). Further analysis suggests that changes in input conditions and technology performance parameters lead to new designs primarily in stage I. Conclusions The proposed framework provides significant insights for technology selection and assists in making informed decisions regarding technologies that should be used in combination for a given set of stream/product properties and final output specifications. Additionally, the parametric sensitivity provides an opportunity to make crucial design and selection decisions in a comprehensive and rational manner. This will prove valuable in the selection of chemicals to be produced using bioconversions (bioproducts) as well as in creating better bioseparation flow sheets for detailed economic assessment and process implementation on the commercial scale. Electronic supplementary material The online version of this article (doi:10.1186/s13068-017-0804-2) contains supplementary material, which is available to authorized users.

The EU Water Framework and Groundwater Directives stipulate that EU member states have to assess groundwater chemical status by the use of groundwater threshold values derived for the protection of dependent ecosystems and human health. In the EU’s 6th FP BRIDGE project ‘‘Background cRiteria for the IDentification of Groundwater thrEsholds’’, a methodology for the derivation of threshold values (TV) for groundwater bodies is proposed. Threshold values are quality standards for polluting substances in groundwater that need to be formulated by the Member States for the status assessment of groundwater bodies. These values represent the concentration of a pollutant that cannot be exceeded in order to protect both the environment and human health. The proposed method derives groundwater threshold values based on environmental objectives for groundwater ”itself” as a receptor, using relevant reference criteria such as natural background levels, drinking and irrigation water standards. This methodology is tested on seven districts in Greece (two of them are analyzed in this paper). Concentrations of major ions, ammonium and data of electrical conductivity were examined. After a pre-selection on databases with groundwater samples the natural background level is determined as the 90- and 97.7 percentile.